Senior AI Engineer
Role details
Job location
Tech stack
Job description
Role Overview: The Senior AI Engineer 1 (Senior Staff) leads the development of advanced AI and machine learning systems with a high degree of autonomy. This role partners closely with architects and product stakeholders to design end-to-end AI solutions, optimize model performance, and ensure scalable, cloud-native deployment. The Senior Staff engineer drives technical decision-making, performs in-depth system analysis, and resolves complex engineering challenges across data, model, and infrastructure layers. The role is responsible for producing high-quality, well-architected solutions and setting technical standards that elevate engineering practices across the team. Senior AI Engineer 1 mentors junior engineers, supports cross-team collaboration, and contributes significantly to roadmap planning. This position establishes itself as a strong individual contributor with deep technical expertise in AI engineering and generative AI technologies.
In this role, you will:
- Design and implement complex AI/ML systems, pipelines, and model-serving architectures for enterprise workloads
- Lead development of reusable frameworks, libraries, and tools to accelerate AI engineering across teams
- Analyze large-scale datasets, model telemetry, and inference performance to drive optimization strategies
- Architect distributed training and model evaluation workflows that improve reliability and accuracy
- Collaborate with senior stakeholders to define solution approaches, technical requirements, and feasibility assessments
- Guide junior and mid-level engineers through design reviews, code reviews, and hands-on technical mentorship
- Implement advanced automated testing, including stress testing, bias detection, non-regression testing, and quality evaluations
- Troubleshoot complex pipeline failures, infrastructure errors, and distributed system bottlenecks
- Document architectural decisions, engineering patterns, and best practices to elevate organizational knowledge
- Optimize performance across all stages of model lifecycle, including preprocessing, training, and inference
- Participate in roadmap discussions and provide expert-level technical recommendations for future AI capabilities
- Ensure alignment with security, compliance, data governance, and responsible AI guidelines
- Research new generative AI, machine learning, and cloud technologies to evaluate applicability to enterprise use cases
- Contribute to incident response and operational support for deployed AI systems, * Basic ML/AI literacy (training vs inference, knowledge cutoffs, LLM fundamentals)
- Prompt engineering and instruction hierarchies
- Context window and context management
- Model selection and capabilities
- Fine-tuning vs prompting vs RAG
- Hallucination and grounding strategies
- Guardrails and output validation
- Evals and testing approaches
- Security and PII awareness
- Responsible AI and governance
- LLM APIs and integration standards
- RAG and vector search
- Vector databases and embeddings
- Agentic workflows and tool use
- Cost and performance awareness
- Common enterprise use cases
Requirements
Do you have experience in Validation design?, Do you have a Master's degree?, * 4-6 years of professional AI/ML engineering or software engineering experience
- Deep proficiency in Python, ML frameworks, and cloud-native engineering
- Strong understanding of distributed systems, data pipelines, and model optimization; ability to lead technical designs and perform advanced debugging
- Advanced hands-on experience with AWS, Azure, or Google Cloud; strong containerization expertise (Docker); production deployment using Kubernetes (EKS/AKS/GKE)
- Proficiency with Terraform and infrastructure automation; deep experience with cloud ML platforms (SageMaker, Vertex AI, Azure ML)
- Hands-on background with GPU/accelerator workflows; building and optimizing distributed training jobs; strong knowledge of observability and monitoring tools
- Expertise with PyTorch and/or TensorFlow; advanced experience fine-tuning transformer architectures using Hugging Face
- Hands-on experience designing RAG systems with vector databases including Pinecone, Weaviate, or FAISS; building GenAI microservices using LangChain or LlamaIndex
- Demonstrated success evaluating and integrating LLM APIs (OpenAI, Azure OpenAI, Gemini); hands-on implementing PEFT and LoRA/QLoRA fine-tuning techniques
- Skilled in designing LLM evaluation suites covering quality, safety, latency, and bias; track record optimizing inference at scale
- Proficiency with low-code platforms including Microsoft Power Platform (Power Apps, Power Automate, AI Builder, Copilot Studio); experience developing APIs and SDKs that enable low-code AI consumption and building agents with multi-step reasoning and tool orchestration
- Effective communication for cross-functional technical alignment; demonstrated ability to work independently and handle complex problems
- Demonstrated ability to own a complete workstream lifecycle with minimal supervision
- Bachelor's degree in Computer Science, Engineering, Data Science, or related technical field; Master's degree or equivalent advanced study preferred
- Travel for this role may be up to 80%, based on client and project needs. Actual travel requirements may vary, * History of leading technical workstreams, mentoring engineers, or driving complex AI projects through full delivery lifecycle
- 2+ years as a senior individual contributor with full-cycle project delivery and business development contribution
- History of supporting sales pursuits or business development initiatives
- Track record of engaging independently with executive or C-suite stakeholders
- Established record of leading process improvement or innovation initiatives
- Confident presenter adaptable to any audience or format
Minimum Knowledge Expectations
All candidates for Crowe Studio positions are expected to demonstrate baseline AI and technical knowledge, regardless of role or level., * Intellectual curiosity - asking thoughtful questions and seeking deeper understanding
- Attention to detail - noticing subtle issues and inconsistencies
- Analytical thinking - breaking down complex problems and thinking critically
- Tenacity - following issues through to resolution, even when challenging
- Strong communication - conveying ideas clearly to technical and non-technical audiences, We are committed to a merit-based hiring process, evaluating all candidates consistently using objective, job-related criteria such as relevant experience, demonstrated skills, measurable impact, and alignment with the role's responsibilities, and making employment decisions in a fair and inclusive manner free from discrimination.
Benefits & conditions
Pulled from the full job description
- Unlimited paid time off